hossamAhmedSalah/computational_intelligence-_project

Clustering-Based Customer Segmentation with CI/EC Algorithms

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Mahdi-toumi/Airline-Customer-Data-Analysis

Airline Customer Data Analysis: An unsupervised analysis project segmenting passengers and identifying satisfaction drivers using PCA, MCA, CAH, and k-means to provide actionable insights for improving customer experience and loyalty.

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Badr-MOUFAD/multivariate-time-series-clustering

Multivariate clustering of weather data. This is part of my research internship.

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abomokh/Kmeans-symNMF

C library implementing KMeans++ and SymNMF algorithms, fully compatible with Python.

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semnan-university-ai/buddymove_holidayiq_clustring 📦

TTSAS - Fuzzy_cMeans - min_proximity - min_proximity

Language: MATLAB - Size: 603 KB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 0

labrijisaad/Git-Clustering

Enhanced and Repackaged GIT Clustering: This repository offers an open-source, enhanced version of the GIT (Graph of Intensity Topology) clustering algorithm.

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JavidChaji/FUM-Computational-Intelligence-Data-Clustering-Based-On-Key-Identification

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sunny-dni/Topic-Dependent-Argument-Mining

My Thesis Project Implementation

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geehaad/ML-Master-Projects

Couple of ML projects implemented during my master journy

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YugalPatil97/Cluster_Analysis

Creating clusters for gobal development measurements

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cominsys/Image-Clustering-with-Optimization-Algorithms-and-Color-Space

Image Clustering with Optimization Algorithms and Color Space - Matlab Codes

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HabibNaeimi/FuzzyClustring

System identification using clustering algorithm for nonlinear control - Fuzzy systems control course project - Petroleum University of Technology

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RazGavrieli/greedy-k-centre-CPP

Graph Theory. Implementation of greedy algorithm to approximate k centeriods. The algorithm is 2-approximate and runs at a polynomial time complexity.

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semnan-university-ai/clustering-tendency 📦

clustering tendency

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MichaelFish199/K-Means-Clustering-Implementation

This repository contains an implementation of the K-Means clustering algorithm in Python. K-Means is an unsupervised machine learning algorithm that finds clusters in an N-dimensional space. The implementation provided in this repository allows users to apply K-Means to their own data sets and visualize the resulting clusters.

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SRIST1608/-NETFLIX-MOVIES-AND-TV-SHOWS-CLUSTERING

I have clustered similar movies and TV Shows available on Netflix taking into account of attributes like Description, Cast, Director, Genre etc of a particular movie/show.

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25khattab/text-classifier

text classification

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salmanmehmood1/Algorithm-Visualizor

Find the shortest path and MST cost using Algorithms Visualization. Seven different algorithms have been used to find MST cost.

Language: Python - Size: 43 KB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 1

noranta4/Multi-domain-social-recommender-system

Multi-domain social recommender system • University project • 2018 - Web & Social information extraction - MSc in Computer Science, II year

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desaiankitb/spark-mllib-medium

This repo shows how to review and derive information from datasets using Python. First, get an overview of data science and how it open source libraries like Python can be used for your data analysis need. Then, discover how to set up labs and data interpreters. Next, learn about how you can use pandas, NumPy, and SciPy for numerical processing, scientific programming, and extensive data exploration. With these options at your disposal, you'll be ready for the following code which focuses on making predictions using machine learning tools, data classifiers, and clusters. The repo concludes with a look at big data and how PySpark can be used for computing.

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Nourshosharah/IBM-DataScience-professional-certificate

my assignment in IBM-DataScience-professional-certificate specialization

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rh01/unsupervised

机器学习Coursera专项课程第四门课程-聚类与检索，代码和作业

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